Colonization and persistence ability explain the extent to which plant species fill their potential range

By Frank M. Schurr, Guy F. Midgley, A. Rebelo, G. Reeves, Peter Poschlod, Steven Higgins. 2007

121 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/f10e3a5a5a9a46c50ea8453aa148a641b410b03e

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Applications of species distribution modeling to paleobiology (2011, background): “Dispersal has also been represented using mechanistic dispersal simulations (Schurr et al., 2007) or complex integrated demographic and dispersal simulations (Nathan et al.”
Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents (2012, background): “…of dispersal is particularly valuable (currently most developed for plants, Nathan et al., 2008) which quantifies how biotic exchange between local communities will depend on interspecific variation in functional traits (Schurr et al., 2007) and environmental variation (Kuparinen et al., 2009).”
Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities (2011, background): “Terrestrial SDMs have been extended to include ecological factors such as dispersal (e.g. Broennimann et al., 2006; Schurr et al., 2007; Smolik et al., 2010) and competition (e.”
Dispersal and demography contributions to population spread of Carduus nutans in its native and invaded ranges (2008, background): “Understanding what drives spatiotemporal dynamics is a crucial aspect of ecology in general ( Schurr et al . 2007; Higgins et al . 2008), and invasive species in particular (Sakai et al . 2001).”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “…bias of records (Phillips et al. 2009); dispersal can be incorporated using estimates of dispersal rates (Midgley et al. 2006), models of dispersal (Schurr et al. 2007), or by linking SDMs to cellular automata (Iverson et al. 2009); evolutionary change might be estimable and included in models…”
The state of plant population modelling in light of environmental change (2008, background): “For example, without understanding the mechanisms of long distance seed dispersal, it is difficult to reliably forecast the dynamics of range shifts (Schurr et al., 2007).”
Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic Regions: Opportunities and challenges (2009, background): “Generic mechanistic models of seed dispersal may provide a means of overcoming this problem (Schurr et al. 2005), and estimates of colonization ability derived from these models explain a substantial part of interspecific variation in current biogeographical distributions (Schurr et al. 2007).”
A physiological analogy of the niche for projecting the potential distribution of plants (2012, background): “High false positives were also reported by Schurr et al. (2007) in a study of range filling in South Africa Proteaceae.”
Estimating demographic models for the range dynamics of plant species (2010, methodology): “, 2005), we restricted dispersal to the 5 ¥ 5 cell neighbourhood of each cell, a typical size for large Fynbos fires (Horne, 1981; Schurr et al., 2007).”
How to understand species’ niches and range dynamics: a demographic research agenda for biogeography (2012, background): “However, mechanistic models can be used to predict plant dispersal at scales relevant for range dynamics from measurements of dispersal traits and dispersal environments (Schurr et al., 2007; Nathan et al., 2008).”